{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Token Frequency in ROCO\n",
    "\n",
    "Overfitting could be caused by low-frequency **TOKEN** in ROCO."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pathlib import Path\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tokenization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from open_clip import SimpleTokenizer, tokenize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tokens: torch.Size([2, 77])\n"
     ]
    }
   ],
   "source": [
    "raw_text = [\"i am raw text\", \"the second raw text\"]\n",
    "# raw_text = [str(self.captions[idx])]\n",
    "tokens = tokenize(raw_text)\n",
    "print(f\"tokens: {tokens.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[42mtext1:\u001b[0m <start_of_text>i am raw text <end_of_text>!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n",
      "\u001b[42mtext2:\u001b[0m <start_of_text>the second raw text <end_of_text>!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n"
     ]
    }
   ],
   "source": [
    "tokens_numpy = tokens.numpy()\n",
    "_tokenizer = SimpleTokenizer()\n",
    "text1 = _tokenizer.decode(tokens_numpy[0])\n",
    "text2 = _tokenizer.decode(tokens_numpy[1])\n",
    "print(f\"\\033[42mtext1:\\033[0m {text1}\")\n",
    "print(f\"\\033[42mtext2:\\033[0m {text2}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_filepath = \"/remote-home/share/medical/public/ROCO/test/radiology/processed_test.csv\"\n",
    "df = pd.read_csv(input_filepath, sep=',')\n",
    "captions = df[\"caption\"].tolist()\n",
    "idx = 0\n",
    "# Take out the idx^th caption\n",
    "texts = tokenize([str(captions[idx])])[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([49406, 46550, 24773,   263,   851,   918,  1093,  1818, 49407,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
       "            0,     0,     0,     0,     0,     0,     0])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "texts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calcuate the word frequency of a single caption\n",
    "def frequency_per_caption(texts):\n",
    "    token_frequency = np.unique(texts.numpy(), return_counts=True)\n",
    "    # 统计 caption 中的 token-frequency\n",
    "    frequency = dict(zip(token_frequency[0], token_frequency[1]))\n",
    "    return frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 8176/8176 [00:02<00:00, 3003.21it/s]\n"
     ]
    }
   ],
   "source": [
    "token_frequency = {}\n",
    "# loop through all captions for overall token frequency\n",
    "for caption in tqdm(captions):\n",
    "    texts = tokenize(caption)[0]\n",
    "    frequency = frequency_per_caption(texts)\n",
    "    # print(f\"frequency: {frequency}\")\n",
    "    for key, value in frequency.items():\n",
    "        if key not in token_frequency:\n",
    "            token_frequency[key] = value\n",
    "        else:\n",
    "            token_frequency[key] += value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len(token_frequency): 8724\n"
     ]
    }
   ],
   "source": [
    "# Num of all unique tokens\n",
    "print(f\"len(token_frequency): {len(token_frequency)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frequency_values: [(17445, 1), (16058, 1), (12931, 1), (21212, 1), (12201, 1), (5641, 1), (17083, 1), (8610, 1), (8685, 1), (12546, 1), (826, 1), (24369, 1), (15906, 1), (3621, 1), (7721, 1), (16368, 1), (29694, 1), (21461, 1), (23430, 1), (2050, 1)]\n"
     ]
    }
   ],
   "source": [
    "# See what the low-frequency words look like\n",
    "frequency_values = sorted(token_frequency.items(), key=lambda x: x[1], reverse=False)\n",
    "print(f\"frequency_values: {frequency_values[:20]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Draw Histgram of Token Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hist_values: 8301\n"
     ]
    }
   ],
   "source": [
    "# print(token_frequency.values())\n",
    "hist_values = [value for value in token_frequency.values() if value < 100]\n",
    "print(f\"hist_values: {len(hist_values)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(token_frequency.values(), bins=200, color='black', alpha=0.7)\n",
    "plt.xlabel('Token Frequency')\n",
    "plt.ylabel('Num of Token')\n",
    "plt.title('Hist of Token Frequency')\n",
    "plt.show()\n",
    "\n",
    "# Use more bins to see details\n",
    "plt.hist(hist_values, bins=200, color='black', alpha=0.7)\n",
    "plt.xlabel('Token Frequency')\n",
    "plt.ylabel('Num of Token')\n",
    "plt.title('Hist of Token Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 8724/8724 [00:00<00:00, 1029314.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "lowfre_tokens: [17445, 16058, 12931, 21212, 12201, 5641, 17083, 8610, 8685, 12546, 826, 24369, 15906, 3621, 7721, 16368, 29694, 21461, 23430, 2050, 2081, 44201, 6065, 6580, 8450, 16666, 19198, 39162, 13831, 6164, 14288, 31008, 32826, 7260, 36834, 9375, 16757, 12266, 2687, 3008, 45702, 23724, 15844, 30454, 2783, 40176, 42715, 16127, 22346, 31523, 16863, 19984, 34249, 15703, 16199, 32591, 1355, 9038, 5012, 25173, 20427, 1845, 22070, 49168, 7973, 30381, 18663, 44250, 6323, 6229, 7718, 29422, 31557, 47349, 13504, 5223, 41243, 47531, 13869, 20391, 7369, 19514, 44262, 22945, 29419, 5130, 9529, 22640, 38773, 38086, 13786, 13601, 14193, 4350, 12079, 30048, 10967, 28449, 23816, 28809]\n",
      "id: [17445]; token: cto \n",
      "id: [16058]; token: vacu\n",
      "id: [12931]; token: jury \n",
      "id: [21212]; token: rhi\n",
      "id: [12201]; token: cycli\n",
      "id: [5641]; token: pier\n",
      "id: [17083]; token: sv \n",
      "id: [8610]; token: rapi\n",
      "id: [8685]; token: unknown \n",
      "id: [12546]; token: mobility \n",
      "id: [826]; token: ell\n",
      "id: [24369]; token: lage \n",
      "id: [15906]; token: stepping \n",
      "id: [3621]; token: introduc\n",
      "id: [7721]; token: vine \n",
      "id: [16368]; token: rf \n",
      "id: [29694]; token: cec\n",
      "id: [21461]; token: infused \n",
      "id: [23430]; token: enu\n",
      "id: [2050]; token: care\n",
      "id: [2081]; token: fel\n",
      "id: [44201]; token: seam \n",
      "id: [6065]; token: waste \n",
      "id: [6580]; token: opti\n",
      "id: [8450]; token: sort \n",
      "id: [16666]; token: batteries \n",
      "id: [19198]; token: sorting \n",
      "id: [39162]; token: obs \n",
      "id: [13831]; token: cas \n",
      "id: [6164]; token: jacket \n",
      "id: [14288]; token: lud\n",
      "id: [31008]; token: loff \n",
      "id: [32826]; token: pist \n",
      "id: [7260]; token: carter \n",
      "id: [36834]; token: substances \n",
      "id: [9375]; token: \"- \n",
      "id: [16757]; token: module \n",
      "id: [12266]; token: protected \n",
      "id: [2687]; token: ona \n",
      "id: [3008]; token: missi\n",
      "id: [45702]; token: paralysis \n",
      "id: [23724]; token: mater \n",
      "id: [15844]; token: misses \n",
      "id: [30454]; token: modes \n",
      "id: [2783]; token: move \n",
      "id: [40176]; token: cultured \n",
      "id: [42715]; token: specimens \n",
      "id: [16127]; token: tura \n",
      "id: [22346]; token: vg \n",
      "id: [31523]; token: butt \n",
      "id: [16863]; token: vos \n",
      "id: [19984]; token: ference \n",
      "id: [34249]; token: kv \n",
      "id: [15703]; token: investigate \n",
      "id: [16199]; token: requested \n",
      "id: [32591]; token: practitioner \n",
      "id: [1355]; token: fav\n",
      "id: [9038]; token: smoking \n",
      "id: [5012]; token: itude \n",
      "id: [25173]; token: disappear \n",
      "id: [20427]; token: admitted \n",
      "id: [1845]; token: prote\n",
      "id: [22070]; token: profiles \n",
      "id: [49168]; token: inscribed \n",
      "id: [7973]; token: induc\n",
      "id: [30381]; token: lms \n",
      "id: [18663]; token: compensation \n",
      "id: [44250]; token: preventable \n",
      "id: [6323]; token: raw \n",
      "id: [6229]; token: (# \n",
      "id: [7718]; token: phen\n",
      "id: [29422]; token: assuming \n",
      "id: [31557]; token: oversized \n",
      "id: [47349]; token: mester \n",
      "id: [13504]; token: brien \n",
      "id: [5223]; token: rich\n",
      "id: [41243]; token: shrinking \n",
      "id: [47531]; token: amina \n",
      "id: [13869]; token: sps \n",
      "id: [20391]; token: complaint \n",
      "id: [7369]; token: printing \n",
      "id: [19514]; token: thumb\n",
      "id: [44262]; token: arose \n",
      "id: [22945]; token: destruc\n",
      "id: [29419]; token: kev \n",
      "id: [5130]; token: angel \n",
      "id: [9529]; token: chrome \n",
      "id: [22640]; token: amped \n",
      "id: [38773]; token: mdc\n",
      "id: [38086]; token: alies \n",
      "id: [13786]; token: plymouth \n",
      "id: [13601]; token: akin \n",
      "id: [14193]; token: tories \n",
      "id: [4350]; token: lit \n",
      "id: [12079]; token: inclusion \n",
      "id: [30048]; token: sag \n",
      "id: [10967]; token: describe \n",
      "id: [28449]; token: crs \n",
      "id: [23816]; token: processed \n",
      "id: [28809]; token: allergic \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# 显示低频词\n",
    "# print(token_frequency[16058])\n",
    "lowfre_tokens = []\n",
    "for key, value in tqdm(token_frequency.items()):\n",
    "    if value == 1:\n",
    "        lowfre_tokens.append(key)\n",
    "\n",
    "num_sample = 100\n",
    "print(f\"lowfre_tokens: {lowfre_tokens[:num_sample]}\")\n",
    "for i in range(num_sample):\n",
    "    decoded_token = _tokenizer.decode([lowfre_tokens[i]])\n",
    "    print(f\"id: {[lowfre_tokens[i]]}; token: {decoded_token}\")\n",
    "\n",
    "# _tokenizer.decode(lowfre_tokens[:num_sample])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 8724/8724 [00:00<00:00, 1072706.99it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lowfre_tokens: [17445, 16058, 12931, 21212, 12201, 5641, 17083, 8610, 8685, 12546, 826, 24369, 15906, 3621, 7721, 16368, 29694, 21461, 23430, 2050, 2081, 44201, 6065, 6580, 8450, 16666, 19198, 39162, 13831, 6164, 14288, 31008, 32826, 7260, 36834, 9375, 16757, 12266, 2687, 3008, 45702, 23724, 15844, 30454, 2783, 40176, 42715, 16127, 22346, 31523, 16863, 19984, 34249, 15703, 16199, 32591, 1355, 9038, 5012, 25173, 20427, 1845, 22070, 49168, 7973, 30381, 18663, 44250, 6323, 6229, 7718, 29422, 31557, 47349, 13504, 5223, 41243, 47531, 13869, 20391, 7369, 19514, 44262, 22945, 29419, 5130, 9529, 22640, 38773, 38086, 13786, 13601, 14193, 4350, 12079, 30048, 10967, 28449, 23816, 28809]\n",
      "decoded_token: !\n",
      "decoded_token: ( \n",
      "decoded_token: cor\n",
      "decoded_token: onal \n",
      "decoded_token: view \n",
      "decoded_token: ). \n",
      "decoded_token: mri \n",
      "decoded_token: axial \n",
      "decoded_token: <start_of_text>\n",
      "decoded_token: <end_of_text>\n",
      "decoded_token: . \n",
      "decoded_token: the \n",
      "decoded_token: and \n",
      "decoded_token: with \n",
      "decoded_token: ted \n",
      "decoded_token: tom\n",
      "decoded_token: image \n",
      "decoded_token: inside \n",
      "decoded_token: large \n",
      "decoded_token: showing \n",
      "decoded_token: edge \n",
      "decoded_token: multiple \n",
      "decoded_token: plain \n",
      "decoded_token: compu\n",
      "decoded_token: liver \n",
      "decoded_token: ography \n",
      "decoded_token: tumor \n",
      "decoded_token: masses \n",
      "decoded_token: enhancement \n",
      "decoded_token: abdominal \n",
      "decoded_token: cavity \n",
      "decoded_token: , \n",
      "decoded_token: a \n",
      "decoded_token: d \n",
      "decoded_token: an\n",
      "decoded_token: in \n",
      "decoded_token: an \n",
      "decoded_token: al \n",
      "decoded_token: as \n",
      "decoded_token: from \n",
      "decoded_token: by \n",
      "decoded_token: fi\n",
      "decoded_token: more \n",
      "decoded_token: ca\n",
      "decoded_token: car\n",
      "decoded_token: stu\n",
      "decoded_token: ous \n",
      "decoded_token: than \n",
      "decoded_token: right \n",
      "decoded_token: la \n",
      "decoded_token: sin\n",
      "decoded_token: left \n",
      "decoded_token: ial \n",
      "decoded_token: gram \n",
      "decoded_token: uses \n",
      "decoded_token: reveals \n",
      "decoded_token: signal \n",
      "decoded_token: arrow \n",
      "decoded_token: magnetic \n",
      "decoded_token: gio\n",
      "decoded_token: consistent \n",
      "decoded_token: oti\n",
      "decoded_token: arter\n",
      "decoded_token: indicated \n",
      "decoded_token: abnormal \n",
      "decoded_token: resonance \n",
      "decoded_token: intrac\n",
      "decoded_token: of \n",
      "decoded_token: ap\n",
      "decoded_token: ity \n",
      "decoded_token: tri\n",
      "decoded_token: ical \n",
      "decoded_token: gene\n",
      "decoded_token: height \n",
      "decoded_token: homo\n",
      "decoded_token: thickness \n",
      "decoded_token: ) \n",
      "decoded_token: 2 \n",
      "decoded_token: segment \n",
      "decoded_token: rca \n",
      "decoded_token: o\n",
      "decoded_token: ol\n",
      "decoded_token: fe\n",
      "decoded_token: po\n",
      "decoded_token: mor\n",
      "decoded_token: pl\n",
      "decoded_token: mb\n",
      "decoded_token: ven\n",
      "decoded_token: before \n",
      "decoded_token: thro\n",
      "decoded_token: shows \n",
      "decoded_token: ysis \n",
      "decoded_token: amount \n",
      "decoded_token: vein \n",
      "decoded_token: thrombo\n",
      "decoded_token: st \n",
      "decoded_token: cy\n",
      "decoded_token: size \n",
      "decoded_token: post\n",
      "decoded_token: operative \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# 看看高频词\n",
    "\n",
    "highfre_tokens = []\n",
    "for key, value in tqdm(token_frequency.items()):\n",
    "    if value > 20:\n",
    "        highfre_tokens.append(key)\n",
    "\n",
    "num_sample = 100\n",
    "print(f\"lowfre_tokens: {lowfre_tokens[:num_sample]}\")\n",
    "for i in range(num_sample):\n",
    "    decoded_token = _tokenizer.decode([highfre_tokens[i]])\n",
    "    print(f\"decoded_token: {decoded_token}\")\n",
    "\n",
    "# _tokenizer.decode(lowfre_tokens[:num_sample])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <Image, Caption> Pairs for Low-frequency Tokens\n",
    "\n",
    "Take a further look into <image, caption> pairs containing low-frequency tokens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image, ImageDraw, ImageFont"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 看看最符合这个 image 的 caption 是什么样的\n",
    "def show_sample(sample_idx):\n",
    "    img = Image.open(df[\"image\"][sample_idx])\n",
    "    text = df[\"caption\"][sample_idx]\n",
    "    print(f\"text: {text}\")\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.imshow(img)\n",
    "    # ax.set(title=text)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "text:  CTO of RCA (closure in the 2nd segment)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_sample(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<start_of_text>axial mri ( coronal view ). <end_of_text>!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_tokenizer.decode(texts.numpy())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
